Meta-data approach to querying multiple biomedical ontologies

ABSTRACT

A method for retrieving information spread across a plurality of different ontologies, including: defining a meta-ontology, wherein the meta-ontology includes high-level properties and their mappings to specific properties defined in a plurality of different ontologies; receiving a question, wherein the question is associated with a high-level property; and providing an answer to the question, wherein the answer is determined by using the meta-ontology.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority under 35 U.S.C. §119 to U.S.provisional application No. 61/473,269 filed Apr. 8, 2011 and U.S.provisional application No. 61/482,660 filed May 5, 2011, thedisclosures of which are incorporated by reference herein in theirentireties.

BACKGROUND OF THE INVENTION

1. Technical Field

The present invention relates to accessing information spread acrossmultiple ontologies for the purpose of performing reasoning tasks.

2. Discussion of the Related Art

Ontologies are rich sources of information that can be exploited forperforming reasoning tasks. An example application is the use ofbiomedical ontologies for reasoning within question answering (QA)systems to assist physicians in making the correct diagnosis andprescribing the right medication. Such a QA system needs to havesufficient access to information regarding anatomy, pathology,pharmacology, and other related domains. While there are ontologies thatcater to each of these individual domains, there is no ontology thatsufficiently covers all these domains. Moreover, the ontologies for theindividual domains do not necessarily contain all the informationrequired by QA systems to effectively assist physicians. Therefore, suchsystems need to both enhance and integrate several biomedicalontologies.

SUMMARY OF THE INVENTION

In an exemplary embodiment of the present invention, there is provided amethod for retrieving information spread across a plurality of differentontologies, comprising: defining a meta-ontology, wherein themeta-ontology includes high-level properties and their mappings tospecific properties defined in a plurality of different ontologies;receiving a question, wherein the question is associated with ahigh-level property; and providing an answer to the question, whereinthe answer is determined by using the meta-ontology.

The high-level properties are based on a set of questions a system isexpected to answer. The high-level properties are mapped to specificproperties that provide answers to the expected questions. Thehigh-level properties are represented in a resource descriptionframework description. The meta-ontology includes information about howto generate queries that are used to retrieve information associatedwith the high-level properties from the ontologies. The queries includeSPARQL queries. Some of the high-level properties are defined forretrieving synonyms of particular entities from the ontologies such thatthe same concept represented as different entities in differentontologies can be identified. The ontologies include medical ontologies.The method further comprises integrating a new ontology into themeta-ontology by updating the meta-ontology.

In an exemplary embodiment of the present invention, there is provided asystem, comprising: a memory device for storing a program; a processorin communication with the memory device, the processor operative withthe program to: define a meta-ontology, wherein the meta-ontologyincludes high-level properties and their mappings to specific propertiesdefined in a plurality of different ontologies; receive a question,wherein the question is associated with a high-level property; andprovide an answer to the question, wherein the answer is determined byusing the meta-ontology.

The high-level properties are based on a set of questions the system isexpected to answer. The high-level properties are mapped to specificproperties that provide answers to the expected questions. Thehigh-level properties are represented in a resource descriptionframework description. The meta-ontology includes information about howto generate queries that are used to retrieve information associatedwith the high-level properties from the ontologies. Some of thehigh-level properties are defined for retrieving synonyms of particularentities from the ontologies such that the same concept represented asdifferent entities in different ontologies can be identified.

In an exemplary embodiment of the present invention, there is provided acomputer program product, comprising: a non-transitory computer readablestorage medium having computer readable program code embodied therewith,the computer readable program code comprising: computer readable programcode configured to perform the steps of: defining a meta-ontology,wherein the meta-ontology includes high-level properties and theirmappings to specific properties defined in a plurality of differentontologies; receiving a question, wherein the question is associatedwith a high-level property; and providing an answer to the question,wherein the answer is determined by using the meta-ontology.

The high-level properties are based on a set of questions a system isexpected to answer. The high-level properties are mapped to specificproperties that provide answers to the expected questions. Thehigh-level properties are represented in a resource descriptionframework description. The meta-ontology includes information about howto generate queries that are used to retrieve information associatedwith the high-level properties from the ontologies. Some of thehigh-level properties are defined for retrieving synonyms to particularwords from the ontologies such that the same entity represented indifferent ontologies can be identified.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a question answering (QA) system and its flowaccording to an exemplary embodiment of the present invention; and

FIG. 2 illustrates a computer system in which an exemplary embodiment ofthe present invention may be implemented.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

In accordance with an exemplary embodiment of the present invention,presented herein is a method for retrieving information that is spreadacross multiple ontologies in the context of building a questionanswering (QA) system. The method involves ontology integration andrun-time SPARQL query generation, both of which are accomplished bydefining a meta-ontology that contains information about variousproperties in the ontologies, the mapping between the properties, andinformation needed to generate SPARQL queries for retrieving informationwith respect to these properties. The method abstracts away the actualontologies as it refers only to the meta-ontology to retrieve therequired information. This implies that new ontologies can be integratedinto the system by simply updating the meta-ontology. The method alsoallows for interoperability between ontologies at the level of ontologyalignment. The method may be appropriate for QA systems that rely onseveral large ontologies. The method was tested by considering theFoundational Model of Anatomy (FMA) ontology, the human diseaseontology, and an ontology that represents certain information from theMerck manual. The meta-data used is tailored for QA systems, but themethod itself can be applied to other applications.

In the method, a set of high-level properties based on the types ofquestions to be answered is defined and an upper ontology that mapsthese high-level properties to properties from individual ontologies iscreated. The mapping is not necessarily one-to-one and can bemany-to-many. The mapping between the properties of individualontologies can be derived from their mapping to the high-levelproperties. As an example, consider the case of answering questions ofthe form “What is a [concept-name]?” For this, a high-level property“definition” is defined and the upper ontology is updated to include themapping between “definition” and the properties of the individualontologies that provide an appropriate answer for a definitionalquestion.

Given this, in order to retrieve the uniform resource identifier(URI)refs of all properties necessary to answer definitional questions,the system can simply query the upper ontology. However, just retrievingthese URlrefs is not sufficient to answer a question and correct queriesneed to be formulated to retrieve the appropriate definitions. In orderto formulate the queries, the knowledge of the structure of theunderlying ontologies is required; this information can also be includedin the upper ontology. The following resource description framework(RDF) description shows a possible mapping from the high-level property“definition” to the property providing definitions in the diseaseontology. It is to be understood that other resource description formatsmay be used here, such as text-based (HTML, XML), or graphical (entityrelationship, object role model). This description also contains thenecessary information to generate the SPARQL queries that can be used toretrieve the definitions. OBOINOWL is an abbreviation forwww.geneontology.org/formats/oboInOwl.

<rdf:Description rdf:about=”OBOINOWL#hasDefinition”>  <hasProperty>definition</hasProperty>  <hasQueryTarget>def</hasQueryTarget>   <hasQueryLine>?x.  ?xrdfs:label ?def.</hasQueryLine> </rdf:Description>

The above is an example of the meta-data that is represented in theupper ontology. It encodes two things:

how a high-level property like “definition” is represented in a specificontology (in this case, OBOINOWL#hasDefinition, which means the property“hasDefinition,” described in the ontology “OBOINOWL”),

<rdf:Description rdf:about=”OBOINOWL#hasDefinition”>  <hasProperty>definition</hasProperty>

and how a SPARQL query fragment can be used to retrieve thatinformation,

<hasQueryTarget>def</hasQueryTarget>   <hasQueryLine>?x.  ?xrdfs:label ?def.</hasQueryLine>

Note that multiple properties in specific ontologies can map to onehigh-level property in the upper ontology. This mapping processabstracts away specific ways in which different ontologies encodeproperties.

The description above indicates that the SPARQL queries needed toretrieve definitions from the disease ontology are of the form

SELECT ?def WHERE { [subject] <OBOINOWL#hasDefinition> ?x.?x rdfs:label ?def. }where “[subject]” is the URIref of the concept in the disease ontologywhose definition has to be retrieved. More specifically, this shows howthe above meta-data is translated into executable code (in this caseSPARQL language) that can retrieve the information corresponding to thehigh-level definition from a particular ontology (in this caseOBOINOWL). Note that “?x. ?x rdfs:label ?def .” corresponds exactly tothe query fragment encoded in the RDF above.

The method presented so far assumes that all the URlrefs correspondingto the concept names in the user's question have been identified.However, this is not trivial since different ontologies might refer to aconcept using different names, and the user can use any of these namesin the question. For example, the Merck manual ontology contains thedefinition for “Atrioventricular block” while the user might formulatethe question as “What is a AV block?” The disease ontology contains thename “AV block” as a synonym for “Atrioventricular block” but does notcontain the definition. So, if the system only gets the URlrefscorresponding to the name “AV block,” it will not be able to answer thequestion. In order to deal with such situations and be able to answerthe question, the system needs to retrieve the URIrefs corresponding tothe “Atrioventricular block” in the Merck manual ontology. This can bedone by first retrieving the synonyms of “AV block” from the diseaseontology and then using them to obtain the corresponding URIrefs fromthe Merck manual ontology. In general, to answer any question about aconcept, the system needs to first retrieve all the synonyms of theconcept name used in the question and then use them to retrieve thecorresponding URIrefs. This is what allows for ontology interoperabilityat the level of ontology alignment.

However, since different ontologies have different structures, queryingfor the synonyms is not straightforward. To address this, the presentinvention defines a high-level property “synonym” and uses the upperontology to represent information about querying for synonyms. Thefollowing description shows one way to represent information aboutretrieving synonyms from the disease ontology.

<rdf:Description rdf:about=”OBOINOWL#hasExactSynonym”>  <hasProperty>synonym</hasProperty>  <hasQueryTarget>syn</hasQueryTarget>  <hasQueryLine>?x.  ?x rdfs:label ?syn.</hasQueryLine></rdf:Description>

Here, it is described how the high-level property “synonym” correspondsto the specific property “hasExactSynonym” from the “OBOINOWL” ontology.

In order to obtain the synonyms, the system can query the upper ontologyto retrieve all the information required to formulate the SPARQL queriesneeded to retrieve the synonyms.

A prototype QA system that uses the method of the present invention toquery multiple biomedical ontologies was implemented. The system answersquestions of the form “What is a [concept-name]?” and “What is/are the[relation-name(s)] of the [concept-name]?” With respect to suchquestions high-level properties such as “definition,” “part,”“location,” “connections” and “affected-organs” were defined, so thatquestions, such as “What is the location of the heart?” and “What arethe affected organs of atrial fibrillation?” could be asked andanswered.

The table below shows some of the mappings for the high-level propertiesdiscussed above. In the table, fma stands for the Foundational Model ofAnatomy ontology, oboInOwl stands for OBO format metamodel, rdfs standsfor an RDF schema and merck stands for an ontology that representscertain information from the Merck manual.

High-Level Property Mapped To definition fma:definition,oboInOwl:hasDefinition, fma:location, merck:hasDefinition,fma:surrounded_by, rdfs:subClassOf location fma:location,fma:surrounded_by, fma:contained_in

The table suggests that in order to answer definitional questions of theform “What is a [organ]?” the system also retrieves information aboutthe type of the organ and some information about the location of theorgan. This is another advantage of the method as it enables differentinformation to be retrieved by simply adding/deleting certain mappings.

The architecture of the QA system according to an exemplary embodimentof the present invention is shown in FIG. 1. In FIG. 1, rectangularboxes represent modules of the system and oval boxes representontologies. Control module 110 controls the entire QA process. Theworking of the system will be illustrated with the help of the examplequestion “What is an AV block?” This question may be input to thecontrol module 110 by a user (path 1). The user's question is passed(path 2) to a natural language parser/question parser 120 that extractsthe reasoning task that needs to be performed, the concept and thehigh-level property corresponding to the information that needs to beretrieved in order to perform the task. This information is provided tothe control module 110 (path 3). For the particular question considered,the question parser 120 recognizes that the question is about theconcept “AV block” and the high-level property “definition.” Inaddition, the question parser 120 recognizes that the reasoning type is“retrieval.” A reasoning engine 130 is invoked with these as input (path4).

The reasoning engine 130 retrieves the URI corresponding to the label“AV block” from ontologies 150 (path 5 and 6). The ontology access isvia a query engine 140 which varies depending on the triple store used.Once the URI is obtained, the reasoning engine 130 queries meta-ontology160 to obtain the information required to formulate the SPARQL queriesneeded to retrieve the synonyms (paths 5 and 7). Using this informationand the concept URI, the reasoning engine 130 formulates the SPARQLqueries and uses them to retrieve all the synonyms of “AV block” and thecorresponding URIs from the ontologies 150 (paths 5 and 6). At thispoint, the reasoning engine 130 has all the concept URIs required toretrieve the definition of “AV block.” In order to actually retrieve thedefinition, the reasoning engine 130 queries the meta-ontology 160 andobtains the query information required to formulate the SPARQL queriesneeded to obtain the definitions (paths 5 and 7). Using this informationand the concept URIs obtained so far, the reasoning engine 130formulates all the necessary SPARQL queries. Finally, the reasoningengine 130 uses these queries to retrieve all the definitions of “AVblock” (paths 5 and 6).

With respect to the specific ontologies considered, the disease ontologycontains “AV block” as a synonym of “Atrioventricular block” but doesnot contain the defmition. However, the Merck manual ontology containsthe definition for “Atrioventricular block.” When the reasoning engine130 obtains all the synonyms of “AV block” and the corresponding URIs,it obtains “Atrioventricular block” as a synonym from the diseaseontology and, as a result, it obtains among other URIs, the concept URIcorresponding to “Atrioventricular block” in the Merck manual ontology.When the reasoning engine 130 obtains the query information forretrieving the definitions, it obtains among others, the queryinformation needed to obtain the definitions from the Merck manualontology. Finally, when the reasoning engine 130 formulates the SPARQLqueries and runs them, it obtains the definition of “Atrioventricularblock” from the Merck manual ontology. The definition is then providedto the user (paths 8 and 9).

As will be appreciated by one skilled in the art, aspects of the presentinvention may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present invention may take the formof an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present invention may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, radio frequency (RF), etc., or anysuitable combination of the foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present invention are described with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article or manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

Referring now to FIG. 2, according to an exemplary embodiment of thepresent invention, a computer system 201 can comprise, inter alia, acentral processing unit (CPU) 202, a memory 203 and an input/output(I/O) interface 204. The computer system 201 is generally coupledthrough the I/O interface 204 to a display 205 and various input devices206 such as a mouse and keyboard. The support circuits can includecircuits such as cache, power supplies, clock circuits, and acommunications bus. The memory 203 can include RAM, ROM, disk drive,tape drive, etc., or a combination thereof. Exemplary embodiments ofpresent invention may be implemented as a routine 207 stored in memory203 (e.g., a non-transitory computer-readable storage medium) andexecuted by the CPU 202 to process the signal from a signal source 208.As such, the computer system 201 is a general-purpose computer systemthat becomes a specific purpose computer system when executing theroutine 207 of the present invention.

The computer system 201 also includes an operating system andmicro-instruction code. The various processes and functions describedherein may either be part of the micro-instruction code or part of theapplication program (or a combination thereof) which is executed via theoperating system. In addition, various other peripheral devices may beconnected to the computer system 201 such as an additional data storagedevice and a printing device.

The flowchart and block diagrams in the figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof code, which comprises one or more executable instructions forimplementing the specified logical function(s). It should also be notedthat, in some alternative implementations, the functions noted in theblock may occur out of the order noted in the figures. For example, twoblocks shown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. It will also be notedthat each block of the block diagrams and/or flowchart illustration, andcombinations of blocks in the block diagrams and/or flowchartillustration, can be implemented by special purpose hardware-basedsystems that perform the specified functions or acts, or combinations ofspecial purpose hardware and computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a,” “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present invention has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Theembodiment was chosen and described to best explain the principles ofthe invention and the practical application, and to enable others ofordinary skill in the art to understand the invention for variousembodiments with various modifications as are suited to the particularuse contemplated.

1. A method for retrieving information spread across a plurality ofdifferent ontologies, comprising: defining a meta-ontology, wherein themeta-ontology includes high-level properties and their mappings tospecific properties defined in a plurality of different ontologies;receiving a question, wherein the question is associated with ahigh-level property; and providing an answer to the question, whereinthe answer is determined by using the meta-ontology.
 2. The method ofclaim 1, wherein the high-level properties are based on a set ofquestions a system is expected to answer.
 3. The method of claim 2,wherein the high-level properties are mapped to specific properties thatprovide answers to the expected questions.
 4. The method of claim 1,wherein the high-level properties are represented in a resourcedescription framework description.
 5. The method of claim 1, wherein themeta-ontology includes information about how to generate queries thatare used to retrieve information associated with the high-levelproperties from the ontologies.
 6. The method of claim 5, wherein thequeries include SPARQL queries.
 7. The method of claim 1, wherein someof the high-level properties are defined for retrieving synonyms ofparticular entities from the ontologies such that the same conceptrepresented as different entities in different ontologies can beidentified.
 8. The method of claim 1, wherein the ontologies includemedical ontologies.
 9. The method of claim 1, further comprisingintegrating a new ontology into the meta-ontology by updating themeta-ontology.
 10. A system, comprising: a memory device for storing aprogram; a processor in communication with the memory device, theprocessor operative with the program to: define a meta-ontology, whereinthe meta-ontology includes high-level properties and their mappings tospecific properties defined in a plurality of different ontologies;receive a question, wherein the question is associated with a high-levelproperty; and provide an answer to the question, wherein the answer isdetermined by using the meta-ontology.
 11. The system of claim 10,wherein the high-level properties are based on a set of questions thesystem is expected to answer.
 12. The system of claim 11, wherein thehigh-level properties are mapped to specific properties that provideanswers to the expected questions.
 13. The system of claim 10, whereinthe high-level properties are represented in a resource descriptionframework description.
 14. The system of claim 10, wherein themeta-ontology includes information about how to generate queries thatare used to retrieve information associated with the high-levelproperties from the ontologies.
 15. The system of claim 10, wherein someof the high-level properties are defined for retrieving synonyms ofparticular entities from the ontologies such that the same conceptrepresented as different entities in different ontologies can beidentified.
 16. A computer program product, comprising: a non-transitorycomputer readable storage medium having computer readable program codeembodied therewith, the computer readable program code comprising:computer readable program code configured to perform the steps of:defining a meta-ontology, wherein the meta-ontology includes high-levelproperties and their mappings to specific properties defined in aplurality of different ontologies; receiving a question, wherein thequestion is associated with a high-level property; and providing ananswer to the question, wherein the answer is determined by using themeta-ontology.
 17. The computer program product of claim 16, wherein thehigh-level properties are based on a set of questions a system isexpected to answer.
 18. The computer program product of claim 17,wherein the high-level properties are mapped to specific properties thatprovide answers to the expected questions.
 19. The computer programproduct of claim 16, wherein the high-level properties are representedin a resource description framework description.
 20. The computerprogram product of claim 16, wherein the meta-ontology includesinformation about how to generate queries that are used to retrieveinformation associated with the high-level properties from theontologies.
 21. The computer program product of claim 16, wherein someof the high-level properties are defined for retrieving synonyms ofparticular entities from the ontologies such that the same conceptrepresented as different entities in different ontologies can beidentified.